The moderating effect of cultural value orientations on behavioral responses to dissatisfactory service experiences

Journal of Retailing and Consumer Services 48 (2019) 247–256

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The moderating effect of cultural value orientations on behavioral responses to dissatisfactory service experiences

T

Klaus Schoefera, , Anders Wäpplingb, Nima Heiratic, Markus Blutd ⁎

a

Newcastle University, United Kingdom Northumbria University, United Kingdom c Queen Mary University of London, United Kingdom d Aston University, United Kingdom b

ARTICLE INFO

ABSTRACT

Keywords: Service failure Dissatisfactory service experiences Cultural value orientations Behavioral responses

The increasing globalization of markets and the ease with which services now cross national boundaries provide a compelling reason for understanding the cultural context of service delivery and consumption. Addressing this particular issue, the current study builds upon and extends an emerging line of academic inquiry by investigating the moderating effects of cultural differences on behavioral responses to dissatisfactory service experiences. Using a cross-sectional survey design, the present study's findings indicate that culture, measured by an individual's cultural value orientation along the Hofstede dimensions of individualism/collectivism, masculinity/ femininity, power distance, uncertainty avoidance and long-term/short-term orientation, has indirect effects on voice, exit, negative word-of-mouth and third-party responses. These findings have significant implications for the theory and practice of international service management.

1. Introduction It is difficult for service providers to guarantee error-free service delivery to all their customers. Thus, behavioral responses to dissatisfactory service experiences (i.e. service failures), such as negative word-of-mouth, complaining, third-party action, reduced willingness to repurchase and the intention to switch service providers are of continuing interest. Also increased globalization and changing customer demographics mean that service managers are more and more concerned with understanding the complexities associated with managing customers from different cultures. Taken together, these factors suggest a practical concern for understanding cultural differences in the nature of customer-service provider relationships in general and their impact on behavioral responses to dissatisfactory service experiences in particular. Despite this practical significance, there has been relatively little scholarly work explicitly considering of the role of culture in relation to behavioral responses to service failure experiences. Existing studies are characterized by several shortcomings since (1) they regularly examine only single cultural dimensions, (2) they largely examine direct effects of country culture, while related literature suggests moderating effects, and (3) they often examine only one behavioral variable of dissatisfactory service experiences.

First, existing research largely centers on the cultural dimension of individualism/collectivism (e.g., Wan, 2013; Hui et al., 2011; Chan and Wan, 2008; Mummalaneni, 2008; Chelminski and Coulter, 2007) and/ or equates nationality with the notion of culture (e.g., Chan and Wan, 2008). This state of affairs is problematic since commonly argued that “culture is a multidimensional construct involv[ing] many aspects other than individualism-collectivism …[and that].. research [should].. include other [!] dimensions to present a more complete [!] picture of cultural influence” (Chan and Wan, 2008, p. 88). Also, “[u]sing national generalizations to explain individual behaviors is an ecological fallacy because country-level relationships are interpreted as if they are applied to individuals” (Patterson et al., 2006, p. 265). By not explicitly examining all of Hofstede's (1991) cultural dimensions and by using nationality or cultural cluster membership (e.g., Harris and Russell-Bennett, 2015) to explain individual behavior, services marketing scholars have failed to adequately model and measure potentially pivotal moderating (cultural) variables. As a direct consequence, our knowledge of the role of culture in shaping behavioral responses to dissatisfactory service experiences remains limited. Second, existing studies largely propose that country culture (e.g., Liu et al., 2001; Ergün and Kitapci, 2018; Ferguson and Phau, 2012) or culture-specific concepts such as ‘face’ (e.g., Qiu et al., 2018) directly

Corresponding author. E-mail addresses: [email protected] (K. Schoefer), [email protected] (A. Wäppling), [email protected] (N. Heirati), [email protected] (M. Blut). ⁎

https://doi.org/10.1016/j.jretconser.2019.02.009 Received 20 May 2018; Received in revised form 13 December 2018; Accepted 13 February 2019 0969-6989/ Crown Copyright © 2019 Published by Elsevier Ltd. All rights reserved.

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impacts outcomes of dissatisfactory experiences. Research on the role of culture in relational marketing suggests that effectiveness of customer satisfaction with a firm depends on country culture (Samaha et al., 2014). The authors propose moderating effects of culture making us assume that also “effectiveness” of dissatisfaction may be moderated in a similar manner. A better understanding of the moderating influence of culture helps us to better understand in which cultures dissatisfactory experiences are more harmful. Third, most studies on cross-country differences of dissatisfactory service experiences examine customer exit behavior as a direct consequence often ignoring other outcomes discussed in the literature such as customer voice and negative word-of-mouth (Malafi, 1990; Singh, 1990, 1988; Hirschman, 1970). One could assume that country culture differentially impacts these outcomes since, customers assess these behaviors differently. While exit is the easiest behavior after a dissatisfying experience, complaining towards the firm bears the risk of potential embarrassment. One could speculate whether some cultures which avoid interpersonal confrontation react more likely with exist instead of voice after the negative incident. The present study contributes to a better understanding of these potential differential effects. Addressing these important shortcomings, our study explicitly considers culture as a multi-dimensional construct and focuses on individual-level cultural value orientations along the Hofstede (2001) dimensions of Individualism/Collectivism, Masculinity/Femininity, Uncertainty Avoidance and Long-term/Short-term Orientation. It examines the moderating effects of such individual-level cultural value orientations on the relationships between customer dissatisfaction and behavioral consequences, and it also proposes differential moderating effects for customer exit, voice, and loyalty. In the section that follows, we provide a classification of behavioral responses to dissatisfactory service experiences. Next, we develop several moderation hypotheses concerning the effect of cultural differences on behavioral responses to dissatisfactory service experiences. Subsequently, we present the study's methodology and follow this by a

in marketplace relationships when customers switch (brands) service providers (Hirschman, 1970, p. 29). According to Davidow and Dacin (1997), this is a behavioral response where the consumer is directly involved in the experience of dissatisfaction and does involve an external social network. Voice – represents complaints directed at individuals or organisations external to the consumer's social circle and directly involved in the dissatisfactory experience (Davidow and Dacin, 1997). Voice response occur when customers communicate their discontent explitely (i.e. complain) to the offending party (Zeelenberg and Pieters, 2004). Third-party action – involve seeking help from parties external to the consumer's social circle with sanctioning power such as a Better Business Bureau, legal agencies or newspapers and are not directly involved in the dissatisfactory experience (Davidow and Dacin, 1997; Chan and Wan, 2008; Singh, 1988). Negative WOM – according to Davidow and Dacin (1997) represents negative communication directed at individuals or organisations that are internal to the consumer's social circle and not directly involved in the dissatisfactory experience (e.g., friends and relatives). This is in line with Richins (1983) and Weinberger et al. (1981) who view it as interpersonal communication concerning an organization and/or its products/services that denigrates the object of the communication (Richins, 1983).1 2.2. Influence of culture on service experiences The literature on the influence of culture on service experience indicates existence of cross-country differences. Zhang et al. (2008) reviewed the literature on cross-cultural service research and indicate that numerous studies related Hofstede's (1991) cultural dimensions to consumers’ service experiences—their expectations, their subsequent evaluations of the service experience, and their reactions to the service experience. These studies relate all of Hofstede's (1991) dimensions (Table 1) to the service experience including (1) individualism-collectivism, (2) uncertainty avoidance, (3) masculinity-femininity, (4) power distance, and (5) long-term orientation of a country culture.

Table 1 Hofstede's Five Cultural Dimensions. Source: Hofstede (1991). Cultural dimension

Description

Individualism-collectivism

Individualism reflects the degree to which personal independence is valued over group membership. Conversely, collectivistic societies value group goals and objectives over individual preferences. Uncertainty avoidance reflects the degree of comfort with ambiguous situations and the extent to which efforts have been made to minimize or avoid these situations. Masculinity reflects the degree to which tough and assertive behavior is encouraged. Conversely, femininity encourages tender and nurturing behavior. Power distance reflects the degree to which hierarchy and unequal distributions of power are accepted Reflects the degree to which short-term pain is accepted in return for long-term gain. Societies with a short-term orientation will be more likely to seek immediate gratification than those with long-term orientation but they are less likely to plan or invest for the future.

Uncertainty avoidance Masculinity-femininity Power distance Long-term/short-term orientation

presentation of the empirical findings. We conclude the paper with a discussion of the findings along with their managerial implications, limitations and propose directions for further research.

First, the individualism-collectivism dimension received most attention so far. For instance, Donthu and Yoo (1998) argue that individuals rated higher on individualism display have higher service quality expectations than customers in collectivistic cultures. In the case of dissatisfactory services individuals from high individualism cultures were found to report more often that they would switch, give negative WOM, or complain than individuals from low individualism cultures (Liu et al., 2001; Liu and McClure, 2001). Customers in collectivist culture were found to more likely to engage in private behavior

2. Literature review 2.1. Behavioral responses to dissatisfactory service experiences In line with much of past research we distinguish between four behavioral responses to dissatisfactory service experiences that dominate the customer dissatisfaction and consumer complaining behavior (CCB) literature (e.g., Wan, 2013; Chan and Wan, 2011, 2008; Zeelenberg and Pieters, 2004; Singh, 1988; Malafi, 1990; Singh, 1900, 1988; Hirschman, 1970): exit, voice, third-party action and negative word-of-mouth (WOM). Exit – occurs when individuals “dissociate themselves from the object of their dissatisfaction” and manifests itself

1 With regards the scenario described in Appendix A, the four postpurchase behavioral responses may manifest themselves in the following ways: a reader of the scenario may intend not to visit the computer shop again in the near future (exit), complain to the computer shop's manager (voice), tell his/her family and friends about the incident (negative WOM), and bring the issue to outside parties, such as the press or a consumer agency (third-party action).

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(WOM or exit) than customers in an individualist culture when being dissatisfied with a service experience (Liu and McClure, 2001). A recent meta-study underlines the importance of relationships in collectivist cultures. The authors argue relational variables influence WOM and customer spending more effectively as the customers’ sensitivity to existing relational bonds increases which is the case for collectivistic cultures (Samaha et al., 2014). Second, uncertainty avoidance is also discussed to be related to the service experience. Individuals rated higher on uncertainty avoidance have higher service quality expectations than customers in collectivistic cultures (Donthu and Yoo, 1998). With regard to their response to poor service, Voss et al. (2004) find that U.K. customers were more tolerant of poor service quality than U.S. customers. The authors explain this observation by referring to the lower uncertainty avoidance of U.K. customers. Liu et al. (2001) also find that individuals from low uncertainty avoidance cultures more often said they would switch in case of poor a service experience, give negative WOM or complain than individuals from high uncertainty avoidance cultures. Third, masculinity-femininity received less attention in cross-cultural service research. One of the few exceptions is Samaha et al. (2014) who argue that the increased salience of relationship factors in customer decision making as femininity increases suggests that strong relationships drive outcomes such as WOM and customer loyalt more effectively in feminine than masculine cultures. Besides these two outcomes, little is know about the influence of this cultural dimension on other outcome variables such as voicing a complaint toward the company or engaging in third-party action. Fourth, the literature indicates that power distance is also related to the service experience. For instance, it is argued that in cultures with greater power distance, respondents were more likely to tolerate failure from more powerful service providers (Furrer et al., 2000). Similarly, Donthu and Yoo (1998) argue that individuals rated lower on power distance have higher overall service expectations (Donthu and Yoo, 1998). Finally, the literature gives some indication of the importance of long-orientation. While Laroche et al. (2004) found that Japanese respondents who are high in long-term orientation expressed lower ratings of quality perceptions under a superior service condition than North Americans, Donthu and Yoo (1998) indicate that individuals who are short-term oriented such as North Amercans display higher service expectations. Thus, literature is inconsistent with regard to this cultural dimension.

Involvement With the Dissatisfaction Involved

Not Involved

Internal

Exit

Negative WOM

External

Voice

Third-Party Action

Involvement of Social Network

Fig. 1. Postpurchase behavioural responses to dissatisfactory service experiences (adapted from Davidow and Dacin (1997)).

for customer dissatisfaction (Fig. 1) to be generally consistent with the findings that high levels of customer dissatisfaction encourages exit, voice, negative WOM communications, and third-party actions (e.g., Johnston, 1998; Ping, 1993; Malafi, 1990; Prakash, 1991; Singh, 1990). As indicated in cross-cultural service research, we also assume these relationships to be moderated by five individual cultural value orientations. Samaha et al.’s (2014) meta-study on the role of country culture in relationship marketing finds relational variables such as trust and commitment to be moderated by culture. Since the relationship marketing literature suggests that the quality of a relationship should be assessed using relational constructs such as trust, commitment, and/ or relationship satisfaction (Palmatier et al., 2006), we also propose that the effectiveness of customer dissatisfaction varies by country culture. Fig. 2 shows the conceptual model and hypotheses of this research. 3.1. Main effects Literature regularly refers to Hirschman's (1970) Exit, Voice, and Loyalty theory to gain a better understanding of customer responses to dissatisfactory experiences with a firm. According to this theory, dissatisfied consumers face three different options exit, voice, and loyalty. Singh (1990) explains that exit is a voluntary termination of an exchange relationship which includes switching to another firm.

Cultural Value Orientations

2.3. Shortcomings of available work focusing on culture's influence on service experiences

- Individualism - Masculinity - Uncertainty avoidance - Long-term orientation - Power distance

The present research highlights the importance of country culture for the customers’ service experience. The present research builds up on these studies and extends them in several ways. First, existing studies often examined only two countries and concluded retrospectively that observed differences were caused by country culture without measuring any of Hofstede's (1991) dimensions (Zhang et al., 2008). Second, those studies that measure country culture regularly focus on selected cultural dimensions such as individualism, without considering the influence of other dimensions. Thus, it is unclear which dimension caused the observed effect. Third, while many authors propose that it may be more difficult to satisfy customers in some cultures making satisfaction less relevant as a predictor in these countries, these studies rarely test the proposed interaction effect. Fourth, studies frequently examine the (direct) impact of culture on customer exit and word-of-mouth, while less is known about customer voice behavior and the likelihood of thirdparty action (Liu et al., 2001; Liu and McClure, 2001).

H2, 3, 4, 5

Tendency to Exist

Voice Dissatisfaction

H1 Negative WOM

Third Party Action

3. Conceptual framework and hypotheses Fig. 2. Conceptual framework.

In line with much of past research, we anticipated the main effects 249

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Customers perceive the exit option as particularly painful since they have to search for alternative providers. The theory also explains that the voice option is viewed from a proactive perspective as any attempt to change rather than escape from a relationship with a service provider. Customers attempt to contact management or anyone who cares to listen to their complaint which also requires some effort on the part of the customers. Finally, customer loyalty is dicussed as a passive response since the customers continue to stick with the dissatisfying provider and suffer in silence. Building upon this theory, Singh (1990) argues that only two of the three options are nonredundant, because the loyalty option is operative when a dissatisfied customer neither exits nor voices. Hence, the author recommends focusing on (a) exit and (b) voice as key consequences of dissatisfactory experiences. In addition, Singh (1988) finds that there is evidence of further dissatisfaction responses such as (c) negative word-of-mouth (complaining to friends and relatives) and (d) third party action which should be considered. Third party action refers to seeking assistance from a third party such as for instance a sanctioning body (Singh, 1988). It is explained that the key hypotheses in Hirschman's (1970) theory easily apply to these two additional outcomes. Thus,

change-oriented (LePine and Van Dyne, 1998). Within social structures and exchange relationships, speaking up is often interpreted as negative because it can threaten coehesiveness (Nemeth and Staw, 1989). We assume that the relationship between dissatisfaction and voice is moderated by all of Hofstede's (1991) cultural dimensions. (a) While collectivitic cultures try to avoid direct confrontation even when being dissatisfied (Hofstede et al., 2010), customers in individualistic cultures are more confrontational and speak ones's mind when being dissatisfied (Hofstede et al., 2010). Thus, we propose dissatisfaction to influence voice more effectively in individualistic cultures. (b) Customers high in masculinity are also discussed to be more confrontational and care less about good relationships with others. Thus, these customers are more likely to complain when being dissatisfied, making dissatisfaction more effective in masculine cultures. (c) Similarly, dissatisfaction is assumed to be more effective in high uncertainty avoidance culutures. These cultures are characterized by a higher tolerance for overt displays of aggression and emotions (Hofstede et al., 2010). (d) Customer satisfaction is also more effective in long-term oriented cultures. Hofstede et al. (2010) explain that disagreements are not regarded as inherently negative and as a result, voice scripts would be regarded as more likely in such cultures (Hofstede et al., 2010). (e) Finally, dissatisfaction is less effective in high power distance cultures. Due to the tendency of service customers in high power distance cultures to consider themselves inferior to a service provider who should be respected and not questioned (Hofstede et al., 2010), dissatisfied customers are less likely to confront service providers. Hence,

H1. Customer dissatisfaction is positively related to (a) customer exit, (b) customer voice, (c) negative word-of-mouth, and (d) third-party action. 3.2. Moderating effects

H3. Cultural value orientation moderates the relationship between customer dissatisfaction and voice, such that the effect of customer dissatisfaction on voice is positively moderated by an individual's (a) individualism, (b) masculinity, (c) uncertainty avoidance, and (d) longterm orientation. The relationship is negatively moderated by an individual's (e) power distance.

Exit. Leaving a service provider is an active response of a customer being dissatisfied which requires some effort. We propose that influence of customer dissatisfaction on customer churn varies by country culture. Samaha et al. (2014) argue that the effectivenes of relational variables (such as customer satisfaction) is impacted by Hofstede's (1991) dimensions. (a) Individualistic customers have a greater drive, self-responsibility, and need for autonomy (Furrer et al., 2000). Thus, we hypothesize that customers in individualistic cultures are more likely to switch when they experience a problem, making customer dissatisfaction more effective in individualistic cultures than in collectivistic cultures (Liu et al., 2001). (b) Customers high in masculinity value loyalty and harmony less than customers high in femininity (Liu et al., 2001). Masculine customers are more likely to discipline service providers by switching to alternatives. Thus, customer dissatisfaction is more effective in masculine cultures than in feminine cultures. (c) The literature argues that customers high in power distance are less likely to feel dependent on a service provider (Liu et al., 2001). Thus, a dissatisfactory experience is more likely to make customers switch to alternatives. (d) Finally, customers in long-term-oriented cultures are discussed to be more pragmatic than customer in short-term-oriented cultures (Hofstede et al., 2010). These customers are willing to invest necessary effort to locate a new service provider. Thus, a dissatisfactory experience is more likely to lead to customer churn in these cultures. (e) Customers high in uncertainty avoidance feel uncomfortable with ambiguity. Since provider switching is associated with uncertainty which makes it undesirable (Hofstede et al., 2010), customers in these cultures are less likely to switch even after a dissatisfactory service experience. Thus, dissatisfaction is less effective in these cultures. Therefore,

3.2.2. Negative Word-of-Mouth Negative WOM is a passive response, which is vague as to the target of behavior and often allows for potential anonymity. Thus, this behavioral response can be considered a more subtle means of responding to a dissatisfying service experience that avoids direct confrontation with service providers. (a) According to Hofstede et al. (2010), truth and honesty are virtues in individualistic cultures even when this means expressing sentiments or experiences that might affect others negatively, whereas direct negative expressions are avoided in collectivistic cultures. Thus, dissatisfaction is more effective individualistic cultures. (b) According to Liu et al. (2001), customers in masculine cultures are less likely to engage in NWOM after a negative service experience than customers in feminine cultures because they are unwilling to ‘look bad in others’ eyes affecting their status. Hence, dissatisfaction is proposed to be less effective in masculine cultures. (c) Customers high in uncertainty avoidance feel threatened by ambiguous or unknown situations which makes them feel more anxious in unpredictable situations (Hofstede et al., 2010). Therefore, they are more likely to seek passive and controllable ways of expressing their dissatisfaction such as negative WOM. Thus, dissatisfaction is more likely to affect negative WOM in cultures high in uncertainty avoidance. (d) Long-term oriented cultures tend to place a considerable importance on the concept of “guanxi” and lifelong personal networks (Hofstede et al., 2010). Negative WOM is a more subtle and potentially anonymous means of responding to a dissatisfying service experience that avoids direct confrontation allowing guanxi and personal networks to be maintained. Thus, dissatisfaction influences negative WOM more strongly in longterm oriented cultures. (e) Hierarchic relationships are at the core of Hofstede's (2010) power distance spectrum in the sense that high power-distance cultures emphasize respect given to authorities. It could be expected that dissatisfaction is less likely to impact negative WOM in high power-distance cultures since this shows a lack of respect.

H2. Cultural value orientation moderates the relationship between customer dissatisfaction and exit such that the effect of customer dissatisfaction on exit is positively moderated by an individual's (a) individualism, (b) masculinity, (d) long-term orientation, and (e) power distance. The relationship is negatively moderated by an individual's (c) uncertainty avoidance. 3.2.1. Voice By definition, voice is assertive and non-conformist in that it is 250

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Therefore,

We employed Qualtrics.com to develop the questionnaire in English and pre-tested it using a sample of international students to ensure clarity and readability of the questions. Respondents were requested to read a booklet in which they were exposed to a service scenario, originally developed by Chan and Wan (2008), describing an outcome failure (Appendix A) and were then asked to complete a questionnaire containing structured questions measuring the constructs of interest in this study. Given the number of independent variables and interactions in the model, we calculated that minimum 450 respondents are required to achieve statistical power over 0.90 following the procedure suggested by Faul et al. (2007, 2009). The adopted sampling procedure generated 486 usable responses across 34 countries with 54% from Asia, 32% from Europe, 10% from North America, and 4% from South American and Africa. Respondents’ age ranged from 18 to 65 years (mean=29), 75% were men, and they typically (72%) had a highereducation degree. While we were unable to control the balance between the respondents’ gender (i.e. male vs female), we examined the potential effect of gender by computing t-tests across different cultural value orientations and the results indicated not significant differences. Further, we examined the potential of common method variance and found no evidence of bias in the sample (please see the Results section). The use of such a non-probability sample for the purpose of the present investigation appeared justified on two grounds. First, given that respondents came from a similar demographic background it ensured that any differences obtained were due to cultural value orientation, as opposed to demographic differences. Second, “… when the research objective is to [exclusively] test theory …, and the researcher intends only to use ‘scientific theory to explain events beyond the research setting,’ (Calder et al., 1981, p. 197), then homogeneous samples are acceptable – even desirable – as they reduce the likelihood that extraneous variables will affect the research results.” (Reynolds et al., 2003, p. 85). This happened to be the case in the present study where the objective was to test the effects of cultural value orientations on behavioral responses to dissatisfactory service experiences. With this type of research, internal validity is of primary importance. Such ‘theory application research’ does not require a representative sample, nor does it require the ability to estimate sampling error, because statistical generalization of the findings is not the goal (Reynolds et al., 2003). “It is the theory that is applied beyond the research setting … [and] homogenous samples are preferred because they provide a stronger test of the theory” (Calder et al., 1981, p. 200).

H4. Cultural value orientation moderates the relationship between customer dissatisfaction and NWOM such that the effect of customer dissatisfaction on NWOM is positively moderated by an individual's (a) individualism, (b) masculinity, (c) uncertainty avoidance, and (d) longterm orientation. The relationship is negatively moderated by an individual's (e) power distance. 3.2.3. Third party action Third party action involves seeking assistance from a third party such as for instance a sanctioning body (Singh, 1988) and it is an active response to a negative service experience. The strength of the relationship between dissatisfaction and third party action is proposed to vary by country culture. (a) The relationship is stronger in individualistic cultures as individualism is linked to unversalism (Hofstede et al., 2010) which means that each consumer should be treated exactly the same. In collectivistic cultures, in which particularism (or preferential treatment for in-group members) is prevalent (Hofstede et al., 2010) dissatisfaction is less likely to lead to third party action. (b) The relationship is proposed to be stronger in masculine cultures, where society tends to take on a corrective role (Hofstede et al., 2010) and the consumer will thus draw support from a third party (such as legal counsel or supervisory body) when feeling dissatisfied. (c) Dissatisfaction is more effective in high power distance cultures, in which the service consumer (typically being the weaker party in the service transaction) seeks out a more powerful third party to help establish justice or to receive reparations for the perceived service failure (Hofstede et al., 2010). (d) Individuals high in uncertainty avoidance orientation prefer rules and regulations and are therefore more predisposed towards using third-party action when faced with a dissatisfactory service experience contrary to individuals being low in uncertainty avoidance. Thus, dissatisfaction is more effective in high uncertainty avoidance cultures. (e) Finally, long-term orientation is expected to negatively moderate the relationship between dissatisfaction and third-party action. Long-term oriented cultures are discussed to a lack of focus on truth (Hofstede et al., 2010). A belief that absolute truth exists can be expected to lead to the more common use of thirdparty action after a dissatisfactory experience as the third party often has the power to officially determine truth and grant its seeker legitimacy and justice. Therefore, H5. Cultural value orientation moderates the relationship between customer dissatisfaction and third-party action, such that the effect of customer dissatisfaction on third-party action is positively moderated by an (a) individual's individualism, (b) masculinity, (c) power distance, and (e) uncertainty avoidance orientation. The relationship is negatively moderated by an individual's (d) long-term orientation.

4.2. Measures Each of the constructs used in the present study were measured with multi-item scales, all of which were adapted from previous studies. Customer dissatisfaction was measured using items adapted from Maxham and Netemeyer (2002) using seven-point scales ranging from “1 =Strongly Disagree” to “7 =Strongly Agree”. The four behavioral responses (to customer dissatisfaction were measured using items adapted by Singh (1988) and Chan and Wan (2008) taping intentions to engage in voice, third-party action, negative WOM and exit responses using ten-point scales ranging from “1 =Strongly Disagree” to “10 =Strongly Agree”. In light of the “ecological fallacy” (Patterson et al., 2006) and the potential danger of predicting individual behavior on the basis of preexisting group-levels, the CVSCALE (Yoo et al., 2011) was used to investigate cultural value orientation at the individual level using five-point scales ranging from “1 =Strongly Disagree” to “5 =Strongly Agree”. This scale has previously been used in service research (e.g., Schoefer, 2010; Patterson et al., 2006) and proven to successfully capture Hofstede's (1991) five cultural dimensions at the individual level (e.g., Yoo and Donthu, 2006). We control for the effects of severity of service failure, face concerns, attitude towards complaining, negative affectivity, and demographic information (e.g., age, gender, nationality, and education) on dependent variables. This study measures failure severity using one item from Tsarenko and Tojib

4. Methodology 4.1. Data collection and sample A cross-sectional survey approach was chosen to examine the effect of culture on behavioral responses to dissatisfactory service experiences. This is a common approach taken in the customer dissatisfaction and service failure literature (e.g., Hui et al., 2011; Chan and Wan, 2008; Chelminski and Coulter, 2007; Mummalaneni, 2008; Zeelenberg and Pieters, 2004; Zeithaml and Bitner, 1996). In order to maximize variance within each cultural value dimension, we collected data from a multicultural sample of consumers across different countries. For data collection, participants were recruited through Microworkers.com, which is an online crowdsourcing marketplace similar to Amazon's Mechanical Turk. These platforms have been found to be viable sources of high-quality data produce large volumes at a significantly lower cost (Braunsberger et al., 2007; Donget al., 2015). 251

252

0.92 − 0.14 0.35** − 0.20** − 0.04 0.32** 0.38** 0.27** − 0.06 0.41** − 0.12 0.27** 0.38** − 0.01 0.21* 0.15* 0.03 − 0.15* 5.22 1.51 0.85 0.92 0.83

0.77 − 0.12 − 0.19* 0.50** − 0.05 − 0.18* − 0.43** 0.41** − 0.10 0.17* 0.12* − 0.04 0.40** − 0.24** − 0.15* 0.05 0.19** 3.66 1.20 0.60 0.85 0.78

2

0.81 − 0.45** 0.07 0.53** 0.41** 0.12* − 0.03 0.36** − 0.10 0.45** 0.46** − 0.02 0.11* 0.07 0.01 − 0.08 5.41 1.20 0.65 0.88 0.82

3

0.74 − 0.29** − 0.35** − 0.21** 0.16* − 0.15* − 0.18* − 0.09 − 0.33** − 0.29** − 0.12* 0.08 0.11 − 0.08 − 0.07 3.51 0.93 0.55 0.83 0.73

4

0.85 0.12* − 0.01 − 0.33** 0.38** − 0.01 0.04 0.21** 0.08 0.35** − 0.17* − 0.21** 0.08 0.25** 3.98 1.43 0.73 0.89 0.81

5

0.76 0.38** 0.01 0.02 0.36** − 0.07 0.44** 0.44** 0.08 0.10* 0.05 0.08 0.06 5.27 1.18 0.57 0.84 0.76

6

0.91 0.14* 0.10 0.56** − 0.06 0.29** 0.29** − 0.08 0.15* 0.10* − 0.01 − 0.16* 5.38 1.50 0.83 0.93 0.90

7

0.94 − 0.37** 0.10 − 0.30** − 0.04 0.14* − 0.31** 0.19* 0.05 − 0.08 − 0.18* 4.69 1.52 0.88 0.96 0.93

8

Notes: Diagonal entries show the square roots of average variance extracted. Others represent correlation coefficients. * and * * indicate that the correlation is significant at 0.05 and 0.01 level (two tail).

1 Dissatisfaction 2 Power distance 3 Uncertainty avoidance 4 Individualism 5 Masculinity 6 Long-term orientation 7 Negative WOM 8 Exit 9 Third party action 10 Voice 11 Failure Severity 12 Face 13 Attitude towards complain 14 Negative affectivity 15 Age 16 Gender 17 Education 18 Nationality Mean SD AVE CR α

1

Table 2 Construct-level measurement statistics and correlation matrix.

0.94 0.19** 0.10 0.13* 0.03 0.25** − 0.14* − 0.06 0.13* 0.16* 3.55 1.47 0.89 0.96 0.94

9

0.91 − 0.09 0.23** 0.30** − 0.07 0.22** 0.07 0.04 − 0.06 4.93 1.56 0.83 0.94 0.90

10

1.00 − 0.07 − 0.06 0.17* − 0.11* 0.04 0.00 0.09 3.63 1.51 1.00 1.00 1.00

11

0.75 0.48** 0.26** 0.08 0.05 0.03 0.04 4.84 1.13 0.56 0.83 0.74

12

1.00 0.08 0.16* 0.08 0.05 0.05 4.98 1.34 1.00 1.00 1.00

13

0.73 − 0.20** − 0.02 0.01 0.16* 3.89 0.96 0.53 0.82 0.73

14

1.00 0.12* 0.10 − 0.25** – – – – –

15

1.00 − 0.03 − 0.21** – – – – –

16

1.00 0.14* – – – – –

17

1.00 – – – – –

18

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Table 3 Test of hypotheses. Dependent variables

Main Variables Dissatisfaction Power distance Uncertainty avoidance Individualism Masculinity Long-term orientation Interaction Effects Dissatisfaction×Power distance Dissatisfaction×Uncertainty avoidance Dissatisfaction×Individualism Dissatisfaction×Masculinity Dissatisfaction×Long-term orientation Control Variables Failure Severity Face Attitude towards complain Negative affectivity Age Gender Education Nationality R2 Adjusted R2

Negative WOM

Exit

Third party action

Voice

0.20 (3.79)* − 0.10 (1.72)* 0.13 (2.42)* − 0.04 (0.74) 0.04 (0.75) 0.17 (2.91)*

0.22 (4.18)* − 0.23 (4.12)* 0.06 (1.16)* 0.11 (2.40)* − 0.10 (1.94)* − 0.05 (1.09)

− 0.03 (0.56) 0.27 (4.91)* − 0.04 (0.76) − 0.04 (0.67) 0.20 (3.62)* 0.01 (0.12)

0.27 (5.65)* 0.04 (0.75) 0.12 (2.08)* − 0.01 (0.04) 0.01 (0.17) 0.16 (2.72)*

− 0.09 (1.72)* 0.09 (1.88)* 0.14 (2.46)* 0.06 (1.18) 0.00 (0.05)

− 0.07 (1.59) − 0.09 (1.74)* − 0.12 (2.51)* − 0.05 (0.98) 0.08 (1.82)**

0.05 (0.89) 0.12 (2.47)* 0.14 (2.81)* 0.03 (0.65) − 0.06 (1.67)*

− 0.14 (2.74)* 0.10 (1.83)* 0.10 (1.98)* − 0.03 (0.58) − 0.02 (0.05)

0.04 (0.93) 0.10 (1.98)* 0.04 (0.72) − 0.09 (2.03)** 0.00 (0.02) 0.01 (0.30) − 0.02 (0.38) − 0.11 (2.65)* 0.31 0.28

− 0.18 (3.97)* − 0.03 (0.65) 0.11 (2.22)* − 0.11 (2.24)* 0.01 (0.37) − 0.07 (1.77)* − 0.05 (1.32)* − 0.04 (0.97) 0.36 0.33

0.03 (0.65) 0.02 (0.35) 0.06 (1.24) 0.03 (0.84) − 0.04 (0.82) 0.03 (0.81) 0.09 (2.40)* 0.01 (0.27) 0.26 0.23

0.01 (0.27) − 0.01 (0.20) 0.05 (1.06) − 0.10 (1.99)* 0.09 (2.48)* − 0.01 (0.26) 0.01 (0.29) 0.03 (0.72) 0.30 0.27

Notes: * indicates that the correlation is significant at the 0.05level (one-tailed).

(2012). Face concerns were measured using four items from Wan (2013) reflecting the extent to which an individual shows regard for protection and enhancement of his/her positive social image. Attitude towards complaing was measured using one item from Bodey and Grace (2007). Finally, negative affectivity was measured using four items from Thompson (2007). All measures, item wordings, and corresponding coefficient alphas are reported in Appendix B.

desirable answers. In addition, respondents were assured of anonymity and confidentiality. Second, we implemented several ex post tests to statistically assess the effect of CMV. First, we performed Harman's (1967) single factor test and found that the largest factor explains 20.64% of the overall variance, which indicates no significant threat of common method bias. Because a single latent factor does not account for the majority of the explained variance, we conclude that CMV does not seem to be a problem in this study. Second, we used CFA as a more sophisticated approach to Harman's one-factor test. In doing so, we loaded all items into one confirmatory factor (χ2/df=10.41, CFI=0.29, TLI=0.25, RMSEA=0.14). Because this latent factor does not account for all marked variables, it offers further confidence that CMV is not problematic (Podsakoff et al., 2003).

5. Results To evaluate the robustness of our measurement scales, we performed a confirmatory factor analysis (CFA) using IBM SPSS AMOS. The measurement model showed a good fit (χ2/df=1059/633 =1.67, p < 0.01; comparative fit index [CFI]=0.96; tucker-Lewis index [TLI] =0.95; root mean square error of approximation [RMSEA]=0.03). The composite reliability of constructs ranged from 0.83 to 0.96, and the item loadings ranged from 0.63 to 0.94 (p < 0.01). Average variance extracted (AVE) ranged from 0.55 to 0.89. We assessed discriminant validity following the procedure recommended by Fornell and Larcker (1981). Discriminant validity of the constructs was satisfactory, as the square root of the AVE (the off-diagonal elements in Table 2) were greater than all individual correlations. Having established the soundness of our measures, we subsequently used them to test our hypotheses (Table 3).

5.2. Hypotheses results We adopted the structural equation modeling, particularly IBM SPSS AMOS, to examine hypotheses. Table 2 illustrates the structural results. Consistent with current literature, the results support H1a, b, and c, as high customer dissatisfaction significantly (p < 0.10) increased the tendency to exit (β = 0.22, t-value=4.18), voice (β = 0.27, tvalue=5.65) and negative WOM (β = 0.20, t-value=3.79). However, the results did not support H3d indicating that dissatisfaction insignificantly influenced third-party action (β = −0.03, t-value=0.56) which could be explained by the fact that third-party action represents a lowfrequency and somewhat extreme behavioral response to a service failure. Hypotheses 2 to 5 predicted that differences in cultural value orientation(s) would moderate the effect of customer dissatisfaction on behavioral response to dissatisfactory service experiences.

5.1. Common method variance This study uses a single key informant to generate data for both dependent and independent constructs, and thus there is a possible threat of common method variance (CMV; Podsakoff et al., 2003). We following Najafi-Tavani (2015) employed multiple remedies to minimize possible concerns. First, in the ex-ante research design stage, we followed systematic questionnaire development procedures to achieve clarity of the measurement items (e.g., academic terms), avoid vague concepts and complicated syntax, and in some cases include explanations of possibly ambiguous terms. Items were randomly placed in the questionnaire to make it difficult for respondents to provide socially

5.2.1. Exit The results supported H2d and H2c, as long-term orientation (β = 0.08, t-value=1.82) positively moderated, while uncertainty avoidance (β = −0.09, t-value=1.74) negatively moderated the relationship between dissatisfaction and exit. However, the results rejected H2a, H2b, and H2e, as individualism (β = −0.12, t-value=2.51) 253

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negatively moderated and masculinity (β = −0.05, ns) and power distance (β = −0.07, ns) insignificantly moderated the relationship between dissatisfaction and exit.

complaint) when things are not quite right to recognize that this propensity may be much diminished among individuals with other cultural values orientations (i.e. low [high] individualistic, long-term, uncertainty avoidance [power distance] orientation – e.g., the majority of Filipinos). Customer support services should take this cultural variation into account and be much more proactive in soliciting a Filipino or Chinese customer's honest evaluation of their service experience. This could perhaps be achieved by asking the customer if they were happy with the service provided. Only with the knowledge that something has gone wrong will the firm be able to have the change to recover the customer from his/her service failure. In order to anticipate and explain customer responses to such dissatisfactory service experiences, service managers are well-advised to get to know their customers’ average cultural value orientations. In accord with Patterson et al. (2006), we argue that with sophisticated Customer Relationship Management (CRM) systems and instant online access to customer profiles, there is no reason why cultural value orientations should not be captured via survey research and added to individual customer profiles. In this way, the findings of our study might usefully in guiding international services management. The present study has several limitations that point to the need for further research. First, because of the correlational nature of this study, no causal inferences of any kind can be drawn. Future research should employ research methods that more readily allow for causal inference. Second, our study examined the influence of cultural factors at one moment in time. However, cultural factors are dynamic influences that interact with situational contigencies to shape attitudes and behavior (Tsai et al., 2006; Blodgett et al., 2015). Therefore, future research should utilize longitudinal research to examine whether and how cultural changes (e.g., through migration) alter the behavioral response to service failures over time. Finally, this investigation was also limited to studying only behavioral responses. However, emotions are also thought to play an important role in shaping consumer behavior (Bagozziet al., 1999) and it has been argued that many customers feel strong emotional reactions in response to service failures (i.e. dissatisfactory service experiences) (Smith and Bolton, 2002; Maute and Dubé, 1999). As there is empirical evidence to suggest that these emotional reactions are subject to cultural influences (Tsai et al., 2006; Soto et al., 2005; Scollon et al., 2004; Oyserman et al., 2002; Mesquita, 2001; Mortenson, 1999; Mesquita and Frijda, 1992), an investigation of the effect of cultural differences on emotional responses to dissatisfactory service experiences appears a natural extension and enrichment of the current research. In this context, future research may find it beneficial to utilize other cultural classification schemes (e.g., those of Schwartz, 1994; Trompenaars, 1993 and Hall, 1976) as well as to consider culture specific concepts such as face. Despite these limitations, the present study expands our current understanding of the effects of cultural differences on behavioral responses to dissatisfactory service experiences in several ways. First, our study indicates that the relationships between the customer dissatisfaction and behavioral responses to service failures are probably universal. That is, ceteris paribus, customers will respond to customer dissatisfaction with higher exit, voice, and negative WOM. However, our study also shows that the extent to which customer dissatisfaction influence a customer's behavioral response to a dissatisfactory service experience is culturally dependent. Finally, the present study illustrates the usefulness of operationalizing and measuring culture at the individual-level rather than adopting a strategy in which ethnic and/or national groups are used as proxies for cultural values, ideas, and practices, implying that one group endorses a particular set of cultural values, whereas the other group does not. Together, these findings should take us closer to understanding how and why people differ in their behavioral responses to dissatisfactory service experiences.

5.2.2. Voice The results supported H3a, H3c, and H3e, as individualism (β = 0.10, t-value=1.98) and uncertainty avoidance (β = 0.10, tvalue=1.83) positively moderated, while power distance (β = −0.14, t-value=2.74) negatively moderated the relationship between dissatisfaction and voice. The results rejected H3b and H3d, as no significant moderation effect was found for masculinity (β = −0.03, ns) and long-term orientation (β = −0.02, ns). 5.2.3. Negative WOM The results supported H4a, H4c, and H4e, as individualism (β = 0.14, t-value=2.46) and uncertainty avoidance (β = 0.09, tvalue=1.88) positively moderated, while power distance (β = −0.09, t-value=1.72) negatively moderated the effect of dissatisfaction on negative WOM. The results rejected H3b and H3d, as no significant moderation effect was found for masculinity (β = 0.06, ns) and longterm orientation (β = 0.00, ns). 5.2.4. Third-party action The results supported H5a, H5c, and H5d, as individualism (β = 0.14, t-value=2.81) and uncertainty avoidance (β = 0.12, tvalue=2.47) positively moderated, while long-term orientation (β = −0.06, t-value=1.67) negatively moderated the effect of between dissatisfaction on third-party action. The results rejected H5b and H5e, as no significant moderation effect was found for masculinity (β = 0.03, ns) and power distance (β = 0.05, ns). 6. Discussion and conclusions This study focused on the moderating effect of cultural differences on behavioral responses to dissatisfactory service experiences. Our findings document that such responses are contingent on individuals’ cultural value orientation along the Hofstede (1991) dimensions of individualism/collectivism, power distance, masculinity/femininity, uncertainty avoidance and long-term/short-term orientation. In line with our formulated hypotheses H1–H4, our results show an indirect influence of culture on behavioral responses to service failure in the form of a moderation of the relationship between customer dissatisfaction and behavioral responses (i.e. voice, NWOM, third-party action and exit). As such, our findings go beyond thoses of previous work which heavily relies on single cultural dimensions (e.g., individualism/collectivism) to explain behavioral response differences to service failures amongst respondents with different nationalities (e.g., Wan, 2013; Chan and Wan, 2008). More specifically, our findings document a much more nuanced (i.e. more cultural dimensions beyond individualism/collectivism play a role) influence of culture. The study's findings raise interesting implications for service managers. First of all, service managers must recognize the multiple cultural dimensions that differentiate among the various responses to dissatisfactory service experiences. The extent of customer dissatisfaction is clearly an important factor in promoting the actions of exit, voice, and negative WOM while and third-party action. However, the cultural value orientation of customers has a (moderating) influence on their response to customer dissatisfaction that should not be ignored. For instance, it appears that customers high (low) in individualistic, longterm and uncertainty avoidance (power distance) orientation (e.g., the majority of individuals from Austria and Germany) are more likely to express their dissatisfaction by voicing their concerns directly to the service provider. Therefore, it is particularly important for service managers who have come to rely on customers to tell them (or lodge a

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Appendix A. Scenario Your computer has broken down. You take the machine to a local compute shop for repair. Since the hard disk is damaged, it takes two days for the shop to get the disk replaced. Two days later, you go back to the shop to pick up the computer. You test the computer at the shop. You find the start-up time is longer than before. Moreover, when you run your favorite program, the computer flashes an error message before execution. Appendix B. Measurement Constructs and manifest variables Power distance People in higher positions should make decisions without consulting people in lower positions. People in higher positions should avoid social interaction with people in lower positions. People in lower positions should not disagree with decisions by people in higher positions. People in higher positions should not delegate important tasks to people in lower positions. Uncertainty avoidance It is important to have instructions spelled out in detail so that I always know what I'm expected to do. It is important to closely follow instructions and procedures. Rules and regulations are important because they inform me of what is expected of me. Instructions for operations are important. Individualism Individuals should sacrifice self-interest for the group. Individuals should stick with the group even through difficulties. Group welfare is more important than individual rewards. Individuals should only pursue their goals after considering the welfare of the group. Masculinity It is more important for men to have a professional career than it is for women. Men usually solve problems with logical analysis; women usually solve problems with intuition. Solving difficult problems usually requires an active, forcible approach, which is typical of men. There are some jobs that a man can always do better than a woman.a Long-term orientation Careful management of money (thrift). Going on resolutely in spite of opposition (persistence). Giving up today's fun for success in the future. Working hard for success in the future. Dissatisfaction As a whole, you're not satisfied with the computer shop. You're unhappy about your overall experience with the computer shop. Exit –Will you visit the computer shop again in the near future? Very unlikely: Very likely Inclined not to: Inclined to Definitely will not: Definitely will Negative WOM– Will you tell your family and friends about the incident? Very unlikely: Very likely Inclined not to: Inclined to Definitely will not: Definitely will Third party action– Will you bring the issue to outside parties, such as the press or a consumer agency? Very unlikely: Very likely Inclined not to: Inclined to Definitely will not: Definitely will Voice –Will you Complain to the computer shop's manager? Very unlikely: Very likely Inclined not to: Inclined to Definitely will not: Definitely will a

Loading

T-value

0.71 0.82 0.79 0.76

20.774 46.144 32.079 29.217

0.78 0.80 0.84 0.82

29.833 26.895 44.987 38.909

0.81 0.72 0.78 0.63

21.788 9.738 21.931 9.145

0.86 0.83 0.87

54.39 37.268 58.908

0.81 0.71 0.70 0.81

28.317 16.83 15.397 31.118

0.93 0.92

95.896 71.649

0.92 0.91 0.90

93.289 65.331 54.715

0.93 0.95 0.94

79.897 126.489 100.008

0.94 0.94 0.94

138.241 108.981 98.328

0.92 0.92 0.89

83.117 85.824 56.816

This item is deleted during the scale purification and CFA process.

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